cambridge computational biology phd

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Cambridge centre for data-driven discovery, c2d3 computational biology.

We are living in a very exciting time for biology: whole-genome sequencing has opened up the field of genome-scale biology and with this a trend to larger-scale experiments, whether based on DNA sequencing or other technologies such as microscopy.  However it is also a time of great opportunity for small-scale biology as there is a new wealth of data to build from: one can turn to a computer to ask questions that previously might have taken months to answer in the laboratory. One of the great challenges for the field is analysing the large amounts of complex data generated, and synthesising them into useful systems-wide models of biological processes. Whether operating on a large or small scale the use of mathematical and computational methods is becoming an integral part of biological research.

There remains a world-wide shortage of skilled computational biologists. An important part of C2D3 Computational Biology is an MPhil course based at the Centre for Mathematical Sciences. The 11-month course introduces students to bioinformatics and other quantitative aspects of modern biology and medicine. It is intended especially for those whose first degree is in mathematics and computer science and others wishing to learn about the subject in preparation for a PhD course or a career in industry. Complementing the MPhil course is the Wellcome Trust PhD programme in Mathematical Genomics and Medicine.  Run jointly with the Wellcome Trust Sanger Institute this programme provides opportunities for collaborative research across the Cambridge region at the exciting interfaces between mathematics, genomics and medicine.

History and financial support 

C2D3 Computational Biology came about by the merger of the Cambridge Computational Biology Institute (CCBI) into C2D3 in 2021. The CCBI was established in 2003 to promote computational biology, interpreted broadly, within the University and in the region. It established (2004) the MPhil in Computational Biology programme, founded (2011) the Wellcome Trust Mathematical Genomics and Medicine 4-year PhD programme, and, among other activities, started a popular computational biology annual symposium. The CCBI was involved in setting up and helping to run the Cambridge Big Data (CBD) Strategic Research Initiative out of which the C2D3 Interdisciplinary Research Centre was formed. Similarly the CCBI was part of the group that helped set up the Alan Turing Institute.  

The CCBI received financial support equally from the four science schools of the University: 

• The School of the Biological Sciences      
• The School of Clinical Medicine      
• The School of the Physical Sciences (via DAMTP, Physics, Chemistry)      
• The School of Technology (via Engineering, Computer Science) 

Space was kindly provided by the Department of Applied Mathematics and Theoretical Physics, within the Centre for Mathematical Sciences. 

MPhil in Computational Biology  

The Cambridge-MIT Institute provided funds to establish the MPhil in Computational Biology and subsequently studentships have been provided by: 

• Biotechnology and Biological Sciences Research Council      
• Cancer Research UK      
• Engineering and Physical Sciences Research Council      
• Medical Research Council      
• Microsoft Research 

MGM PhD Programme 

The PhD programme in Mathematical Genomics and Medicine is funded by the Wellcome Trust.

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Quantitative Biology Seminar

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The evolution of gene regulation, compensation and expression noise

Intrinsic disorder promotes protein refoldability and enables retrieval from biomolecular condensates.

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The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

• Supports and connects the growing data science and AI research community 
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PhD in Scientific Computing

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Information on how to enter our PhD programme

A common route for admission into our PhD programme is via the Centre’s MPhil programme in Scientific Computing. The MPhil is offered by the University of Cambridge as a full-time course and introduces students to research skills and specialist knowledge. Covering topics of high-performance scientific computing and advanced numerical methods and techniques, it produces graduates with rigorous research and analytical skills, who are formidably well-equipped to proceed to doctoral research or directly into employment in industry.

List of the groups who offer PhD positions in Scientific Computing and its applications

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We provide training in the areas of bioinformatics and computational biology through short, intense practical courses.

Such training targets primarily life scientists, at graduate and postgraduate level, and covers six major areas:

Basic skills and programming

Courses are led by trainers from the University of Cambridge and collaborating institutions, including the European Bioinformatics Institute , the Wellcome Trust Sanger Institute and the Babraham Institute .

Following the above links, you will find detailed information on our courses and you will be able to book a place, or register your interest for an event, through the University Training Booking System .

Visit the Graduate Admissions web site for more information on our Masters and PhD programmes. The Cambridge Computational Biology Institute (CCBI), based in the Centre for Mathematical Sciences, has relevant Masters and PhD programmes, with faculty drawn from medicine, biology and physical sciences.

Bioinformatics Training Facility

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Department of Computer Science and Technology

Computational biology group members.

This page contains a list of the current and past members of the Computational Biology Group, which is itself part of the Artificial Intelligence Group of the Computer Laboratory .

Each person's name is followed by their CRSid (if they have one) and their office number in the William Gates Building .

The easiest way to contact someone is by e-mail. Computer Laboratory e-mail addresses are of the form crsid @cam.ac.uk or [email protected].

Current Members

Academic staff, research associates, research students, past members, master's students, undergraduate students.

• © 2022 Department of Computer Science and Technology, University of Cambridge

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The School of Biological Sciences offers postgraduate students the opportunity to work with world leading scientists to expand knowledge and understanding across all aspects of biology.  Our researchers are making advances in animal, human, plant and microbial science, from the molecular and cellular levels through to tissues, organs, whole organisms, populations, ecosystems, biodiversity, and human behaviour.

Postgraduate courses in the biological sciences.

Details of the Masters courses and PhD opportunities in the Biological Sciences can be found on the University of Cambridge Postgraduate Admissions website  and are easily searchable via the online course directory .  In addition, postgraduate applicants can search for funding via the University’s Funding Portal . Potential postgraduate supervisors and their areas of expertise can be accessed via the Postgraduate School of Lifesciences  website.  This site also hosts information on researcher development and funding opportunities for postgraduate students within the Postgraduate School of Life Science, which comprises both the School of Clinical Medicine and the School of Biological Sciences.

Funding Support

School of biological sciences masters bursary.

Applicants to taught MPhil courses based in the School of Biological Sciences, who have received a conditional offer of admission to start in October 2023, are eligible to apply for a School of Biological Sciences Master’s Bursary Award in support of their studies here at Cambridge, subject to eligibility criteria. The Bursary Awards, which are aimed at applicants from low-income households with experience of educational disadvantage, provide a top-up maintenance grant (c.£5,000) to support living expenses when a postgraduate Master’s loan or grant is taken with Student Finance England, Student Awards Agency Scotland, Student Finance Wales or Student Finance NI.

Doctoral Training Partnership (DTP)

The School of Biological Sciences, in collaboration with several University of Cambridge departments, Partner Institutes and Cambridge colleges and support from the BBSRC, have come together to create funding packages to support students in the biosciences. These BBSRC DTP studentships offer the opportunity to study for a 4-year funded PhD degree and undertake professional development and training opportunities. More information can be found on the Cambridge Biosciences DTP website .

Alexander Crummell Scholarships 2024 (MPhil and PhD)

In collaboration with Queens’ College, Cambridge, the School of Biological Sciences is inviting applications for the Alexander Crummell MPhil and PhD Scholarships. These scholarships are aimed at Home (UK fee rate) students with Black or Black-Mixed ethnicity, applying for an MPhil or PhD degree in a science-based subject at the University of Cambridge. The terms of the award include that you will become a member of Queens’ College, Cambridge. Find out more about about MPhil Scholarships and PhD Scholarships .

Research Culture and Environment

The School of Biological Sciences is committed to enabling a collaborative, inclusive and diverse working and research environment where all individuals can thrive.  We are an open and welcoming community of researchers, staff and students united in our passion for biological research and academic excellence. 

The School is aligned with the University’s Equal Opportunities Policy , committing to a pro-active and inclusive approach to equality, which supports and encourages all under-represented groups, promotes an inclusive culture, and values diversity.  Ongoing challenges such as the global pandemic and the UK’s departure from the European Union will not change this outlook, and we continue our commitment to welcoming students from around the globe to study here in Cambridge. More information for international and EU postgraduate students can be found on the International Students Webpages .

The School of Biological Sciences is committed to widening participation in postgraduate studies at the University of Cambridge. The Experience Postgrad Life Sciences Summer Internship programme offers paid 8-week long research internships to UK and Republic of Ireland residents who are studying at a UK or Republic of Ireland university for their undergraduate bachelor degree.  This is a unique opportunity to interact with both postgraduate students and academics.  You can find out more on the Experiences Postgraduate Life Sciences website .

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The MPhil in Biological Sciences by Advanced Study is a full-time programme offering students the opportunity to undertake a period of study and lab-based research in an area of scientific importance and interest. Applications now open!

Cambridge Biosciences DTP PhD Programme

The Cambridge Biosciences Doctoral Training Partnership offers fully funded four-year PhD Studentships in the Life Sciences. The programme focusses on interdisciplinary training, skills development and provides opportunities to work with industry partners.

Postal Address: School of the Biological Sciences 17 Mill Lane Cambridge CB2 1RX Information provided by:     [email protected]

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Computational and Systems Biology PhD Program

Computational and systems biology.

The field of computational and systems biology represents a synthesis of ideas and approaches from the life sciences, physical sciences, computer science, and engineering. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created new opportunities to understand biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are newer in biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, mathematics, and computer science. Graduates of the program are uniquely prepared to make novel discoveries, develop new methods, and establish new paradigms. They are also well-positioned to assume critical leadership roles in both academia and industry, where this field is becoming increasingly important.

Computational and systems biology, as practiced at MIT, is organized around "the 3 Ds" of description, distillation, and design. In many research programs, systematic data collection is used to create detailed molecular- or cellular-level descriptions of a system in one or more defined states. Given the complexity of biological systems and the number of interacting components and parameters, system modeling is often conducted with the aim of distilling the essential or most important subsystems, components, and parameters, and of obtaining simplified models that retain the ability to accurately predict system behavior under a wide range of conditions. Distillation of the system can increase the interpretability of the models in relation to evolutionary and engineering principles such as robustness, modularity, and evolvability. The resulting models may also serve to facilitate rational design of perturbations to test understanding of the system or to change system behavior (e.g., for therapeutic intervention), as well as efforts to design related systems or systems composed of similar biological components.

CSB Faculty and Research

More than 70 faculty members at the Institute participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering, providing CSB students the opportunity to pursue thesis research in a wide variety of different laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision by faculty members with different areas of expertise. Areas of active research include computational biology and bioinformatics, gene and protein networks, regulatory genomics, molecular biophysics, instrumentation engineering, cell and tissue engineering, predictive toxicology and metabolic engineering, imaging and image informatics, nanobiology and microsystems, biological design and synthetic biology, neurosystems biology, and cancer biology.

The CSB PhD Program

The CSB PhD program is an Institute-wide program that has been jointly developed by the Departments of Biology, Biological Engineering, and Electrical Engineering and Computer Science. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged.

CSB Graduate Education

All students pursue a core curriculum that includes classes in biology and computational biology, along with a class in computational and systems biology based on the scientific literature. Advanced electives in science and engineering enhance both the breadth and depth of each student's education. During their first year, in addition to coursework, students carry out rotations in multiple research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to conduct thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their teaching and communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research to prepare them for the complexities and demands of modern scientific research. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.

The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that is selected by each student in consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, while at the same time providing oversight and guidance to ensure that training is rigorous and thorough.

Core Curriculum

The core curriculum consists of three classroom subjects plus a set of three research rotations in different research groups. The classroom subjects fall into three areas described below.

Modern Biology (One Subject): A term of modern biology at MIT strengthens the biology base of all students in the program. Subjects in biochemistry, genetics, cell biology, molecular biology, or neurobiology fulfill this requirement. The particular course taken by each student will depend on their background and will be determined in consultation with graduate committee members.

Computational Biology (One Subject): A term of computational biology provides students with a background in the application of computation to biology, including analysis and modeling of sequence, structural, and systems data. This requirement can be fulfilled by 7.91[J] / 20.490[J] Foundations of Computational and Systems Biology.

Topics in Computational and Systems Biology (One Subject): All first-year students in the program participate in / 7.89[J] Topics in Computational and Systems Biology, an exploration of problems and approaches in the field of computational and systems biology through in-depth discussion and critical analysis of selected primary research papers. This subject is restricted to first-year PhD students in CSB or related fields in order to build a strong community among the class. It is the only subject in the program with such a limitation.

Research Group Rotations (Three Rotations): To assist students with lab selection and provide a range of research activities in computational and systems biology, students participate in three research rotations of one to two months' duration during their first year. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

The requirement of four advanced electives is designed to develop both breadth and depth. The electives add to the base of the diversified core and contribute strength in areas related to student interest and research direction. To develop depth, two of the four advanced electives must be in the same research area or department. To develop breadth, at least one of the electives must be in engineering and at least one in science. Each student designs a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.

Additional Subjects: As is typical for students in other doctoral programs at MIT, CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics relevant to the student's thesis research in later years. The CSB Graduate Committee works with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.

Training in the Responsible Conduct of Research: Throughout the program, students will be expected to attend workshops and other activities that provide training in the ethical conduct of research. This is particularly important in interdisciplinary fields such as computational and systems biology, where different disciplines often have very different philosophies and conventions. By the end of the fourth year, students will have had about 16 hours of training in the responsible conduct of research.

Qualifying Exams: In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination at the end of the second year or the beginning of the third year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis research, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.

Thesis Research: Research will be performed under the supervision of a CSBi faculty member, culminating in the submission of a written thesis and its oral defense before the community and thesis defense committee. By the second year, a student will have formed a thesis advisory committee that they will meet with on an annual basis.

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Computational and Biological Learning Laboratory

The Computational and Biological Learning Laboratory uses engineering approaches to understand the brain and to develop artificial learning systems. Research includes Bayesian learning, computational neuroscience, statistical machine learning, and sensorimotor control.

The work of the Machine Learning group is very broad, including all aspects of probabilistic machine learning, ranging from studying fundamental concepts in Bayesian statistics to achieving competitive performance of the group’s algorithms in big-data applications. Topics include machine hearing and vision, information retrieval, learning for control, and bioinformatics.

The work on human learning includes both computational modelling and experimental approaches using robotic and virtual reality interfaces. Using the formal approaches of computational neuroscience, a discipline that studies the nervous system through mathematical models, the group aims to both understand the fundamental organising principles of the brain and to employ these to build more efficient machines. As the superiority of biological systems over machines is rooted in their remarkable adaptive capabilities, the group’s research is focussed on the computational foundations of biological learning.

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gene expression and regulation •DNA, RNA, and protein sequence, structure, and interactions • molecular evolution • protein design • network and systems biology • cell and tissue form and function • disease gene mapping • machine learning • quantitative and analytical modeling

David Bartel

Christopher burge, olivia corradin, amy e. keating, eric s. lander, douglas lauffenburger, gene-wei li, adam c. martin, sergey ovchinnikov, david c. page, peter reddien, francisco j. sánchez-rivera, brandon (brady) weissbourd, jonathan weissman, harikesh s. wong, michael b. yaffe.

Francisco J. Sánchez-Rivera aims to understand how genetic variation shapes normal physiology and disease, with a focus on cancer.

In immune cells, X marks the spot(s)

Gene silencing tool has a need for speed

CHARMed collaboration creates a potent therapy candidate for fatal prion diseases

She’s fighting to stop the brain disease that killed her mother before it gets her

“Rosetta Stone” of cell signaling could expedite precision cancer medicine

Taking RNAi from interesting science to impactful new treatments

Q&A: Pulin Li on recreating development in the lab

Scientists develop a rapid gene-editing screen to find effects of cancer mutations

MPhil in Biotechnology

Bringing together world-leading academics and industry champions to deliver state-of-the-art education at the interface of biology with the physical sciences and technology..

Image © Martin Bond

About the programme

Interdisciplinary training for the biotech sector and beyond.

Some of the most important frontiers of biology are at the interface with the physical sciences and technology.

Our MPhil in Biotechnology programme aims to respond to major talent needs in academia and industry by teaching students who have strong analytical skills how to apply them in biotechnology and allied sectors. The programme is particularly suited to those with a degree in engineering, physics, chemistry, maths or computer sciences, but it is also open to candidates with other backgrounds wanting to combine numerical and biological reasoning.

This is an 11-month full-time programme, running from October to August, which combines taught and research elements and delivers a very interdisciplinary curriculum. 

World-renowned interdisciplinary expertise

The programme draws on the world-class research and teaching expertise in biotechnology-related areas at the University of Cambridge. It is primarily based at the Department of Chemical Engineering and Biotechnology (CEB) but is tightly coupled to other departments within the University, including Engineering ,  Physics , Applied Mathematics and Theoretical Physics , Chemistry ,  Materials Sciences and Metallurgy , Plant Sciences , Pharmacology , Biochemistry , and Genetics , which contribute to teaching and/or host research projects in the respective areas of expertise. The programme also relies on close links with industry champions.

The MPhil in Biotechnology provides all-round training covering four key areas:

In addition to theoretical knowledge, we ensure that our students acquire the necessary practical skills in biotechnology both for wet-laboratory and computer-based work. Throughout the programme, we place significant emphasis on the development of research skills, including critical thinking, documenting and reporting, academic writing and communication, and research management. The fast-paced, demanding and competitive environment in which biotechnology research and commercialisation takes place calls for business-savvy scientists, be it in academia or industry. Our programme also offers a range of opportunities for students to acquire business-relevant knowledge and skills.

Overall, our goal is to produce graduates with fundamental and advanced understanding of biotechnology that have the necessary skillset and business acumen to become future leaders in biotechnology either in academic or industrial settings.

Industry links

While the academic environment at the University of Cambridge provides an invaluable and incomparable learning experience to our students, we also ensure that the training we provide is strongly connected to industry.

Our students have plenty of opportunities to benefit from input from industry experts in order to understand the biotech industry landscape and boost their professional networks.

We are proud to be supported by a diverse group of industry champions as well as the Milner Therapeutics Institute , whose goal is to coordinate companies and academic, pharmaceutical and biotechnology partners in a global therapeutic alliance.

Our industry champions are part of our Strategic Committee, playing a role in the direction of the programme. Their input is useful to ensure that the training we provide not only is academically sound, but is also aligned with workforce needs, current practices and developments in industry. Furthermore, our industry champions, as well as number of local biotech companies, contribute to teaching by delivering lectures and seminars on specific topics as well as hosting and supervising research projects (individual and team projects). 

Programme content

The four key learning areas of the programme are explored through six complementary elements with taught, practical and research formats..

1. Core biotechnology course 

At the start of the programme, students take a compulsory taught course on principles of biotechnology. This is a broad-spectrum course that progresses from the fundamentals of molecular and cell biology to more advanced topics on synthetic biology, transgenic animals, plant biotechnology, biological warfare, forensic molecular biology and environmental biotechnology.

The aim of this course is to equip students with the biological language and reasoning necessary for them to effectively apply their analytical skillset in biology-related areas.

2. Practical course

The practical module complements the core lecture course in giving students a strong foundation in modern biotechnology. Over approximately 50 hours, students learn essential and state-of-the-art techniques in biology research, developing practical skills through both taught and hands-on elements. 

The course involves both computer-based sessions, covering DNA design and analysis software, and wet-lab sessions, where students have the opportunity to execute a range of molecular and cellular biology protocols as well as attend demonstrations on specific tools.

Examples of techniques covered in the practical course include:

• molecular cloning,
• CRISPR-Cas9,
• bacterial transformation,
• DNA sequencing and analysis,
• recombinant protein expression and purification,
• cell culture,
• mammalian cell transfection
• and fluorescent lifetime imaging microscopy.

3. Elective advanced courses 

The programme offers students the possibility of tailoring their studies to their educational needs and career goals. In addition to the foundational biotechnology modules, students take six elective courses, which they can choose from a list of subjects taught at CEB and at other departments across the University. These courses allow students to acquire advanced knowledge and skills in specific fields close to their interests. 

Students can select their advanced courses along three axes – analysis, application and business – with the following options being normally available*:

* Please note that the courses on offer may change slightly from year to year, subject to, for example, student numbers and academic staff availability.

 Analysis-oriented courses

Biophysics (CEB) 

The aim of this course is to provide an understanding of how to model biological systems and make them amenable for quantitative exploration. The course introduces the students to quantitative biology and leads them through the process of examining life from a biophysicist’s perspective applying thermal and statistical models to living systems. In the course, the students also learn the principles behind various biophysical and optical techniques and explore specific applications of those techniques in living systems.

Mathematical biology of the cell (Department of Engineering)

The course covers topics in stochastic processes and statistical mechanics with application in biology. It introduces the students to sub-cellular processes and the role of thermal fluctuations, addresses the shift from the classical biology approach to a more physical description of the relevant processes, and illustrates the use of mathematical/computing approaches to study regulatory networks and biomolecular dynamics.

Cellular and molecular biomechanics (Department of Engineering) 

This course deals with the relation between the microstructure of soft biological materials and their mechanical properties. In the course, the students get a working understanding of the various components within plant and animal cells, cytoskeletal components in particular, explore key mechanical properties of cells and tissues, and study muscles as actuators at the tissue, cell and protein length scales. 

Computational neuroscience (Department of Engineering)

This course covers basic topics in computational neuroscience and demonstrates how mathematical analysis and ideas from dynamical systems, machine learning, optimal control and probabilistic inference can be applied to gain insight into the workings of biological nervous systems. The course also highlights a number of real-world computational problems that need to be tackled by any ‘intelligent’ system as well as the solutions that biology offers to some of these problems.

Materials and molecules: modelling, simulation and machine learning (Department of Engineering)

This course introduces the concept of computer simulation of material and molecular properties on the atomic scale, teaching basic techniques of molecular dynamics and data analysis and providing hands-on experience with commonly used software packages. The students are first guided through fundamental modelling concepts, ranging from quantum mechanics and statistical mechanics to the practicalities of numerical simulation, multiple length and time scales and error control. Then, they learn about specific models for materials and molecules that facilitate calculation of basic properties of matter, allowing both a deeper understanding of experimental observations and first principles prediction of new phenomena. The final section of the course addresses machine learning and how it allows breaking previously established limitations of numerical approaches, both for direct first principles dynamical simulations and using statistical ‘data mining’ methods.

Systems biology (Department of Applied Mathematics and Theoretical Physics)

This course covers kinetic design principles in cells, deterministic rate equations, stochastic processes, master equations, the Gillespie algorithm, linear noise approximation, performance bounds and trade-offs in control and biological model systems (e.g. bacterial gene expression, plasmids). Single cell and single molecule experiments and synthetic biology are also covered.

Optical microscopy (CEB)

This course focuses on the fundamental principles of optical microscopy, covering image formation, the physical concepts that affect image resolution and contrast, and quantitative image data analysis in the presence of noise. Modern microscopy technologies that are used in research and industry are described, and students learn about the process of conceptually designing advanced instrumentation that meets the requirements of a given application.

Application-oriented courses

Bionanotechnology (CEB) 

This course explores bionanotechnology, an interdisciplinary field at the interface of nanotechnology and bioscience, and looks into bionano hybrid design and applications. In the course, the students learn about the fundamental principles of nanoengineering, including nanomaterial preparation, assembly and characterisation, get an overview of the scales of biomolecular systems, and explore strategies to join biointerfaces with engineered components. DNA nanotechnology, bioinspired catalysts, biosensors and nanomedicine are embedded throughout the course to give an overview of the potential, advantages and challenges that need to be overcome in bionanotechnology.

Biomimetics (Department of Engineering)

This course explores the idea of adopting and adapting ideas from nature to make new engineering entities, putting a strong emphasis on the interdisciplinary communication between engineers and biologists. In the course, the students learn how to plan and conduct biomimetic research by having the opportunity to examine a number of projects and applications, namely bioinspired legged locomotion, biomimetic adhesion and adhesives, orthotic design and assessment, biomimetic flight dynamics, and biomimetic materials for mechanical support and for visual appearance.

Biomaterials (Department of Materials Science and Metallurgy)

This course starts by addressing the relationship between structure and properties in soft natural materials, including proteins, polysaccharides, and composites of proteins and polysaccharides. Then, it explores the issues involved in the design of a material to replace a failed natural material in a medical context. Emphasis is put on soft tissue replacement, including spinal disc replacement, vascular grafts, skin grafts and tissue engineering scaffolds. Drug delivery systems, particularly those for controlled delivery, are also covered in the course.

Chemical biology and drug discovery (Department of Chemistry) 

In this course, key biological systems are used to explain ideas about the interplay between structure, function and inhibition in chemical biology. The course also highlights chemical strategies that allow for site-selective protein modification and how these are being used to provide biological insight and for the construction of protein conjugates for therapeutics. The science behind the different approaches adopted by academia and the pharmaceutical industry in the early stages of drug discovery are also discussed.

Biosensors and bioelectronics (CEB and Department of Engineering)

This course covers the principles, technologies, methods and applications of biosensors and bioelectronics. The first part of the course gives an overview of biosensing and the application of principles of engineering to the development of biosensors, electrochemical and optical biosensors in particular. In the second part of the course, students are introduced to bioelectronics and learn about implantable electronic medical devices and wearable devices.

Medical physics (Department of Physics)

This course gives an overview of the use of physics in medicine. Particular attention is given to medical imaging, and contrast mechanisms, data acquisition hardware and the general principles of image reconstruction are covered for a range of clinically applicable techniques. Clinical applications of physics, including in diagnosis, patient monitoring and treatment of diseases, are also described. 

Pharmaceutical engineering (CEB) 

This course aims to give students an understanding of the fundamentals of pharmaceutical engineering. It introduces the subject and builds on established concepts from general chemical engineering to highlight specific applications and requirements of this industrial sector. The students learn about the design of solid dosage forms and modified released technologies and explore current trends in pharmaceutical processing.

Healthcare biotechnology (CEB)

This course aims to lay a foundation in the prevalence, pathologies, diagnosis and treatment of the major diseases afflicting humans in the 21st century. The course covers the challenges encountered in drug discovery and development, drug delivery, regulation and the newer approaches involving gene, protein, cell-based and bionic therapies. Key developments for the future, including AI, stratified and personalised medicine, and digital health applications, are also discussed.

Business-oriented courses

Strategic management (Department of Engineering; Judge Business School)

This course provides students with an opportunity to discuss the strategic challenges faced by managers in today’s business environment and to develop a facility for critical strategic thinking. Students become familiar with key strategic analysis models, understanding their application and limitations, and explore some of the current hot topics in strategic management. 

International business (Department of Engineering; Judge Business School)

This course aims to provide future managers with an enhanced understanding of international business by covering globalisation, socio-cultural and political variation in business environments, and international business strategy. The course moves beyond the analysis of market opportunities and industry competitiveness by paying extensive attention to the social, political and cultural differences that businesses need to consider when their activities cross borders. An appreciation of this broader ‘institutional’ environment is essential for managers in order to accurately identify international opportunities and threats. 

Management of technology (Department of Engineering; Institute for Manufacturing)

This course addresses the ways in which technology is brought to market by focusing on key technology management topics from the standpoint of an established business as well as new entrepreneurial ventures. Emphasis is placed on frameworks and methods that are both theoretically sound and practically useful. Through the course, students will not only understand the core challenges of technology management, but also acquire practical means of dealing with them.

Innovation and strategic management of intellectual property (Department of Engineering; Institute for Manufacturing)

This course builds on the state of the art in strategic IP management thinking for maximising appropriation value from technological innovations. While the course emphasises a management perspective on intellectual property, it also includes concepts from engineering, law and economics. 

4. Individual research project

The MPhil in Biotechnology is a taught programme with a strong research component, which includes an individual research project and a team research project.

From the start of the programme until early summer, students undertake an individual research project, which allows them to extend their specialised knowledge by exploring a topic of their choice, develop practical skills in wet-lab and/or computer-based environments, and acquire a range of technical and transferable skills that will set them up for independent research. 

Depending on the student's specific interests, the individual research project may be based at CEB, other participating University departments and/or a site of one of our industry partners. All projects have a supervisor who is an academic at the University of Cambridge. Co-supervisors, from academia or industry, may also be involved. 

This element of the programme requires students to plan and execute their own work, and analyse, interpret and critically discuss their results, which are submitted in the form of a final report. Normally, students also write a review paper and deliver oral and poster communications as part of the individual research project.

Candidates are not required to identify their topic of research at the time of application for the MPhil in Biotechnology. Each year, students are provided with a list of projects to choose from. The list of projects is put together in the summer before the start of the programme and includes titles proposed by academics from departments across the University as well as our industry champions. If candidates have specific research interests, we are happy to discuss those during the admission process.

Examples of individual research project titles in previous years:

• Lab-on-chip sensor for electrochemical biosensing of bone health (CEB)
• Enhancing a locally manufacturable CRISPR-Cas12a based assay for typhoid fever diagnostics (CEB)
• Transcriptional response to amyloidogenic proteins in mammalian cells (MRC Toxicology Unit)
• DNA origami nanostructures for the targeted destruction of bacteria (CEB)
• Kinetic modeling of Chinese hamster ovary metabolism (GSK and CEB)
• Visualising tumour vascular microenvironment (Cancer Research UK Cambridge Institute and Department of Physics)
• 3D-printed microfluidic structures towards exosome-based point-of-care diagnostics (Mursla and Department of Physics)
• Novel approaches to increase high-value compounds in microalgae (Department of Plant Sciences)
• Drugging the undruggable: combining large scale omics data with machine learning techniques to identify novel E3 ligases for PROTAC drug discovery (Milner Therapeutics Institute)
• Measuring action potentials with nanopipettes in photoactivated neurons (CEB)
• Classification of plant diseases through combination of image analysis and environmental data (NIAB and CEB)
• Development of graph-based computational methods for the design of custom organic chemical syntheses (AstraZeneca and CEB)
• How do bacteria age? Studying senescence and death in microbes (Department of Engineering)
• Developing a toolbox for probing protein homeostasis in naked mole-rats (Department of Pharmacology)
• Antagonism of TLR4 as a novel therapy for inflammatory diseases (Department of Veterinary Medicine and CEB)
• Influence of calcification and heparin coating on polymeric prosthetic heart valves (CEB)
• Design of robust multivariate predictive models for process analytics in the biopharmaceutical industry (GSK and CEB)
• Synthetic biology for diterpenoid metabolic engineering in the marine diatom Phaeodactylum tricornutum (Department of Plant Sciences)
• Modelling FRET to estimate bacterial dynamics in vivo (Department of Veterinary Medicine)
• Scaling the production of pluripotent stem cell-derived skin organoids (STEMCELL Technologies and CEB)
• Exploring the multivalent nature of CTPR proteins to study liquid-liquid phase separation (Department of Pharmacology)
• Contractility measurements in tissue engineered constructs (CEB)
• Nanodiamond probes for characterisation of P-granules (Department of Physics and CEB)
• Using computational biology to identify novel therapeutic targets for ion channels-related disease (LifeArc and Milner Therapeutics Institute)
• Engineering of imine reductases to elucidate sequence-structure-function relationships (Johnson Matthey and CEB)
• Machine learning for phage protein classification and de novo design (Nemesis Bioscience and Department of Genetics)

5. Team research project

Over the summer, the whole class works collectively in the team research project, which is a distinctive feature of the MPhil in Biotechnology. Often, the team research challenge is organised in collaboration with one of our industry partners; sometimes we set it in an applied context of sustainable development, working with NGOs. Students plan and deliver the project together, supported by an academic supervisor and experts from industry and/or other external organisations. Strong emphasis is put on team-driven and peer-to-peer learning. The class is required to manage and effectively capitalise on the individual technical and management strengths of each student to complete the challenge.

In this element of the programme, students have the chance to further develop technical and practical competences in biotechnology as well as transferable skills. The team research project is also key to the acquisition of business-relevant knowledge as students work on a problem that is motivated by the needs of a contributor from industry or other external organisation. Students rely on leadership competences, effective project management, multilingualism to understand a range of different stakeholders, and commercial awareness to successfully complete the exercise.

The team research project culminates in the delivery of a report and an oral presentation to the project sponsor. 

Titles of the team projects completed by previous cohorts:

2018-2019: Predictive development of complex biopharmaceuticals. The cohort spent the summer at MedImmune/AstraZeneca.

2019-2020: A systems biology approach to investigate the role of cholesterol in neurodegenerative diseases. The cohort produced a business plan for a software start-up in addition to tackling the scientific challenge.

2020-2021: Circular design of a CRISPR toolkit for the SDGs. The cohort designed a manufacturing toolkit for CRISPR-based biosensors for improved access and capacity building in low-resources contexts. Additionally, the students worked with end-user researchers and educators from Kenya, Ghana, Cameroon and Ethiopia to produce educational materials for HE providers and governmental research institutions in these countries.  

2021-2022: Design of devices for procurement and preservation of organs for transplantation. The cohort worked in collaboration with the Royal Papworth Hospital, which is one of the world's leading cardiothoracic hospitals and the UK's main heart and lung transplant centre. In addition to the technical development of new systems, the students produced a whitepaper on ethical considerations around heart transplantation and assessed the commercial viability of one of the new products they worked on. 

6. Professional and career skills module

In addition to providing strong scientific and technical training in biotechnology, the programme intends to help students to develop competences and a mindset that ensure a smooth transition from university education to the workplace. Transferable and business skills training is central to various elements of the programme and further promoted by a dedicated module running throughout the year. 

This module covers professional skills all the way from the lab bench to the market. At the start of the module, emphasis is put on research skills in areas such as research management, academic writing and presentations, and the publishing process. Then, students are guided through the journey of turning lab research into marketable products and have the opportunity to hear about a range of aspects relevant to the development of new biotech products (e.g. intellectual property, regulatory affairs, science diplomacy and bioethics). The module also includes sessions on careers, addressing careers advice, entrepreneurship and biotech contributions to UN Sustainable Development Goals.

This module was created to complement the core, advanced and practical biotechnology knowledge that is acquired in the other elements of the programme, and it is tightly integrated with the programme’s research component, with some research skills sessions being specifically designed to support students with aspects of the individual and team projects.

Teaching and assessment

In line with the programme structure, teaching is delivered through a combination of formal lectures, practical classes, supervised research in one-to-one and group settings, and a range of other means supporting the development of practical and transferable skills (e.g. training workshops, seminars, formal and informal presentations). 

The taught courses are assessed through a combination of some or all of the following:  individual or group coursework, class participation, formal written examination, and individual or group presentations.

The programme’s research component is examined by appraisal of reports and oral presentations taking place during the MPhil in Biotechnology Symposium at the end of the programme.

In order to be awarded the MPhil degree, the students need to pass satisfactorily both the taught and research components of the programme.

Programme management

Gabriele Kaminski Schierle, Programme director

Gabi is a lecturer in Molecular Biotechnology, the head of the Molecular Neuroscience Group , and co-director of the Cambridge Infinitus Research Centre . As the director of the MPhil in Biotechnology, she is devoted to providing the best training for the future biotech leaders. Gabi studied biology at the University of Fribourg in Switzerland and did her PhD in Medicine on neural transplantation in Parkinson's disease at Lund University in Sweden. She has since set-up a centre for the application of modern biophysical methods for the study of the molecular mechanisms causing neurodegenerative diseases. Gabi loves to ski with her family, is very European, enjoys art, neuroscience and theatre.

Raquel Costa, Programme manager

Raquel gained her PhD from the University of Cambridge working with Professor Geoff Moggridge in the Structured Materials group . She was then a researcher and a lecturer at the University of Coimbra before relocating to Cambridge in 2015. In her research, Raquel merged her background in chemical engineering with biological and environmental sciences to focus on the problem of invasive biofouling bivalves. She also has a longstanding interest in the interface between higher education and the labour market, and has been involved with the EFCE in efforts to develop chemical engineering education in the face of new employment challenges. Prior to joining the MPhil in Biotechnology, Raquel worked at the University's Institute of Continuing Education as an analyst supporting the development of new programmes. She loves to travel and read, but when she is not at work, she will probably be with her two little rascals baking with too much brown sugar or crafting with too much glitter (and hopefully not the other way round).

Teaching and project supervision

Sebastian Ahnert

Sabine Bahn

Somenath Bakshi

Department of Engineering

Sarah Bohndiek

Department of Physics

Graham Christie

Ljiljana Fruk

Jim Haseloff

Department of Plant Sciences

Florian Hollfelder

Department of Biochemistry

Laura Itzhaki

Department of Pharmacology

Janet Kumita

Kathryn Lilley

Mick Mantle

Gos Micklem

Department of Genetics

Geoff Moggridge

Róisín Owens

Olivier Restif

Department of Veterinary Medicine

Steve Russell

Alison Smith

Sam Stranks

Graham Treece

Axel Zeitler 

Strategic Committee

A committee composed of academics and industry representatives with varied expertise and research interests contributes to the strategic management of the programme. Below is a list of the current members of the programme’s Strategic Committee, where the Programme Director and the Programme Manager also sit:

Alison Smith: She is Professor of Plant Biochemistry and Head of the Department of Plant Sciences. Alison's research group focuses on several aspects of the metabolism of plants, algae and bacteria, in particular vitamin and cofactor biosynthesis, using synthetic biology approaches to develop algae as novel production platforms for high value products. She is the Director of the Algal Innovation Centre, a facility that allows growth of algae at scale under natural conditions in collaboration with industry. Andy Sederman. He is Reader in Magnetic Resonance in Engineering and the Deputy Head of Department for teaching matters at CEB. Andy's research interests lie in the development and application of magnetic resonance methods to process and reaction engineering, in particular the understanding of multi-component reaction, diffusion and flow processes.

Annette Alcasabas: She is a Lead Scientist at Johnson Matthey. She has a background in microbial genetics and is interested in technologies that improve commercial enzyme production, enzyme discovery and protein engineering. Chris Howe. He is Professor of Plant Biochemistry and Group Leader at the Department of Biochemistry. His group's overall research theme is the biochemistry and molecular evolution of photosynthetic organisms. One of the group's achievements has been the discovery of a novel cytochrome in plants and green algae (cytochrome c6A), whose function they are still investigating. Their research interests also extend to the manipulation of algae photosynthetic machinery for the production of renewable energy as well as chloroplast genome and its evolution.

Clemens Kaminski: He is Professor of Chemical Physics and Head of Department in CEB. His group develops advanced photonic technologies for the study of molecular mechanisms of disease. He has published more than 200 papers, serves on numerous scientific advisory boards, and is a Fellow of the Optical Society of America.  

Gos Micklem: He is Director of the Cambridge Computational Biology Institute, based in the Department of Applied Mathematics and Theoretical Physics. Gos is also a member of the Department of Genetics where his group is based, with interests in integrative genomics, through the InterMine project, and in synthetic biology.

Graham Christie: He is a Senior Lecturer at CEB, where he also leads the Molecular Microbiology Group. As a microbiologist, Graham is particularly interested in bacterial spore germination processes, which his group investigates at the molecular level using a range of approaches, including genetic, biochemical, crystallographic and advanced imaging techniques. 

Jim Haseloff: He is a Professor at the Department of Plant Sciences and Head of the Synthetic Biology and Reprogramming of Plant Systems Group. With a history of research in plant viroids, RNA enzymes and engineering approaches to plant development, Jim is currently interested in simple open systems for plant synthetic biology. Jim is Chair of the Steering Committee of the Synthetic Biology Interdisciplinary Research Centre.

Kathryn Chapman: She is the Deputy Director of the Milner Therapeutics Institute. Prior to joining the Institute, Kathryn was Head of Innovation and Translation at NC3Rs. She holds an honorary professorship with the University of Coventry, where she sits on the Vice-Chancellors Advisory Group for industry/academic engagement. As a researcher at the University of Manchester, Harvard Medical School, Wellcome Trust Sanger Institute and GlaxoSmithKline, she focused on the genetics of osteoarthritis and transgenic models for drug development and disease modelling.

Kathryn Lilley: She is the Professor of Cellular Dynamics at the Department of Biochemistry, where she also directs the Cambridge Centre for Proteomics. Her research programme aims to create and apply technology to measure the dynamics of the proteome and transcriptome in high throughput in space and time during critical cellular processes. Her group has also contributed with many open-source informatics tools to efficiently mine and visualise the complex data produced by spatiotemporal proteomics studies. She has published more than 250 peer reviewed papers. In 2017 she was the recipient of the Juan Pablo Albar Proteome Pioneer Award from the European Proteomics Association, and in 2018 she received the HUPO Distinguished Achievements in Proteomics award. She was elected as a member of EMBO in July 2020.

Ljiljana Fruk: She is a Reader in BioNano Engineering at CEB. With a background in chemistry, biospectroscopy and nanotechnology, Ljiljana leads the BioNano Engineering Group, and she is interested in the use of bio and nanoelements to design materials for catalysis, drug delivery and tissue engineering.

Namshik Han: He is the Head of Computational Biology and Artificial Intelligence at the Milner Therapeutics Institute. After obtaining a PhD in Machine Learning and Computational Biology from the University of Manchester, Namshik has been a researcher at Samsung, back at the University of Manchester, and at the University of Cambridge, where he is now leading the computational biology and artificial intelligence strand at the Milner Therapeutics Institute.

Rob Clemmitt: He is Vice President, Head of Cell & Gene Therapy (CGT) Medicine & Process Delivery (MPD) in Medicinal Science & Technology (MST) in R&D at GlaxoSmithKline. In this role, he leads the CMC/supply chain leaders responsible for global projects from candidate selection to commercialisation. He also supports the development of the vector, cell, formulation and testing approaches and the autologous supply chains for the TCR-T assets. He is also leader to the global MPD team for the aSARS-CoV-2 mAbs (VIR-7831 & 2, anti-spike protein mAbs) that are being developed in collaboration with VIR Biotechnology. He has 25 years experience of medicine research, development, registration and commercialisation, including cell and gene therapies, biopharmaceuticals and small molecules. He holds a PhD, an MA and a BA in Biochemical Engineering from the University of Cambridge.

Róisín Owens: She is a Professor and the Head of the Bioelectronic Systems Technology Group at CEB. Her current research interests lie on the application of organic electronic materials for monitoring biological systems in vitro, with an emphasis on the gut-brain-microbiome axis. Róisín has received several awards, including the ERC starting (2011), proof of concept (2014) and consolidator (2016) grants, a Marie Curie fellowship, and an EMBO fellowship.

Sara Serradas Duarte: She is the Research Strategy Manager of Cambridge Global Challenges (CGC). Sara has a background in life sciences – she studied biotechnology and microbiology in Portugal and France and neuroscience at the University of Cambridge. Having grown up in Mozambique, she has always had a strong commitment to advancing the contribution of University-generated knowledge to development priorities in low-income countries. This is achieved at CGC through the mobilization of academic (STEM and AHSS) and cross-sectoral (e.g. policy-making, civil society, business) expertise in research programmes co-developed with colleagues in the Global South. Prior to joining CGC, Sara founded secondGO, a social start up that extends the educational opportunities of university students to others, and worked as a Business Analyst and Educational Content Developer for WaterScope, a Cambridge-based start-up that combats water inequality through a 3D printed water-testing microscope. 

Steve Russell: He is a Professor and Head of Department in the Department of Genetics. Steve's lab explores aspects of transcriptional regulation and chromatin architecture at a genome wide scale in Drosophila. His group has a long-standing commitment to the provision of community resources for the fly, and they have contributed to several resource projects including DrosDel, FlyChip and modENCODE. Steve is involved in the Grand Challenges in Global Health programme to develop novel methods of controlling the malaria vector Anopheles gambiae.

Meet our students and alumni

The MPhil in Biotechnology puts together a group of highly capable and motivated students from a range of academic and career backgrounds, from all over the world. Many wish to merge their expertise in engineering, physics, chemistry, maths or computer sciences with biotechnology. Others have research and/or employment experience in the bioscience sector. They all are committed to become highly regarded players in biotechnology research and industry. The class size varies from year to year but is typically between 14 and 18 students.

Diversity at entry and a very interdisciplinary programme mean even more diversity at departure – since they left the MPhil in Biotechnology, our alumni have been pursuing a very wide range of careers in academia, large multinationals, small start-ups or the consultancy sector, among others.

Alumni benefits

As a University of Cambridge alumnus/a you will be entitled to a range of benefits , such as the official alumni card that instantly identifies you as a member of the University (CAMCard), a free email for life exclusive for our graduates, and access for life to our Careers Service.

The CEB Alumni Relations  team works at the CEB level to further promote the connection between the Department, its current members and its alumni.

As part of your learning experience with us, you will also become a member of our own MPhil in Biotechnology Alumni Network. We value alumni as an important part of the growing MPhil in Biotechnology community. After you leave the programme, we would like to keep hearing from you, and we hope you will continue being involved in our community, follow CEB’s achievements, participate in our activities, share your experiences, support future programme editions and inspire the new students. We also hope that the MPhil in Biotechnology Alumni Network will help you keeping in contact with your classmates as well as extend your professional network.

Testimonials

Ana mihai (romania, class of 2021-2022).

My background is in Computer Science, which I studied at undergraduate level, and I had over 5 years of experience as a software engineer in industry before deciding to take a different path in my career.

I wanted to apply and augment my existing skills and experience in a new field, so I was interested in finding a course which would give me a technical understanding and grounding in the latest advances, thus enabling me to achieve this ambition. I chose the MPhil in Biotechnology firstly due to the breadth of topics it covered in its taught component, which equipped me with relevant knowledge and practical skills. Secondly, the research component was a great opportunity to experience doing research in academia, allowing me to make a more informed decision when choosing what opportunities to pursue afterwards. Lastly, Cambridge being at the heart of an important European biotech cluster offered me the chance to expand my network of connections.

Personally, one of the things I really enjoyed about the MPhil was the practical course, as it was the first time I was in a wet lab and I learned a lot. Another advantage of the MPhil is the flexibility to tailor it based on the specific topics you want to explore, by choosing the relevant electives. I really enjoyed getting to know and also work with my cohort, especially during the group research project. While Cambridge can sometimes feel quite small, the Colleges offer many opportunities for interesting activities, ranging from sports to arts. London is also just an hour away by train!

In the near future, I will continue to expand my knowledge and skills while working within a research environment, by learning new molecular biology lab techniques and applying my existing programming skills within the new context of bioinformatics.

Bhavik Kumar (Malaysia, Class of 2021-2022)

I graduated in mechanical engineering, and then went on to predominantly work in the energy industry with ExxonMobil and Petronas for a few years.

The MPhil in Biotechnology programme stood out to me as an avenue to leverage my engineering knowledge and converge into the biomedical sector, something I have wanted to do. Additionally, Cambridge as a city is rapidly growing as a biotech hub, and so we had access to professionals in the industry either through the course or the university's societies and outreach programmes.

I joined the course as a Chevening scholar, and had an amazing year. I enjoyed the vibrant life in Cambridge, and I am very appreciative to have been there post-Covid. The course itself is well curated and gave us exposure to a variety of subjects and ideas in the field. I enjoyed meeting with other students in the cohort from different academic backgrounds, which added so much richness and sparked enjoyable conversations with different perspectives. 

The wide range of interdisciplinary course modules gave me insight into specific concepts I am very excited about, and I hope to continue pursuing some of those branches professionally.

I also enjoyed the individual research project; apart from the opportunity to work with academics and students at the bleeding edge of science, I got a first-hand glimpse of how to navigate through a research-dominated environment, which I thoroughly benefitted from.

The next step I hope to take is to work in the research and design of medical devices.

Yicheng Liu (China, Class of 2021-2022)

With a quantitative undergraduate degree in finance and risk management, I worked as a life science investor and advisor for four years before joining the MPhil in Biotechnology programme. During my work experience, I realised the importance of advanced scientific knowledge in translating biomedical technologies into therapeutics. This motivated me to seek structured academic training in bioscience, and the MPhil in Biotechnology was the perfect platform for me to solidify my life science knowledge base.

The half-taught, half-research approach was what made the programme intellectually challenging and rewarding. For instance, from the core module lectures, I acquired a broad spectrum of fundamental knowledge on molecular and cell biology. Such knowledge played an essential role in the subsequent individual research project, as it further deepened my understanding of cutting-edge bioscience concepts and enabled me to apply my analytical skills into the research topic. This interplay between lectures and independent research was an incredible highlight of my MPhil experience.

Meanwhile, I have also met so many lovely and smart classmates and lab mates. I absolutely enjoyed my journey at Cambridge, especially the collaborative and supportive culture within my cohort and in the research lab where I conducted my supervised research project.

After graduating, I moved to the University of Oxford to pursue further studies in integrated immunology. I look forward to further exploring the life science field using the biotechnology knowledge and skillset that I have gained at Cambridge.

Jakob Traeuble (Germany, Class of 2021-2022)

Before starting the MPhil in Biotechnology, I completed a Bachelor’s degree in Physics at the University of Munich. I was always fascinated by the astonishing developments and breakthroughs in biotechnology and thus wanted to apply my analytical skillset in this exciting field. The very broad range of research subjects and the interdisciplinary approach were key factors for me to choose the MPhil in Biotechnology.

Cambridge is a truly impressive place to study, and I thoroughly enjoyed immersing myself in college life.

In the programme, I focused on the science and computational aspects. I particularly enjoyed the computational neuroscience course. Within the individual research project, I used novel machine learning methods to study neuronal activity. This strategy can be used to investigate brain phenomena in more detail such as the mechanisms behind neurodegenerative diseases. The aspect I liked the most about this MPhil is its multidisciplinary. This shows in the incredible range of electives and research topics as well as the cohort itself.

After finishing the programmme, I am staying in the Department of Chemical Engineering and Biotechnology to pursue a PhD in Biotechnology, for which I have been awarded a Gates Cambridge Scholarship. Based on my previous research in the MPhil, I am analysing correlatively the link between brain elasticity and neuronal activity in neurodegenerative diseases.

Michelle Silver (US, Class of 2021-2022)

After completing my undergraduate degree in Robotics and Control Engineering from the U.S. Naval Academy, I was motivated to pursue my interest in biotechnology, broaden my perspectives, and deepen my intercultural competency.

Overall, the MPhil program was both demanding and enriching. Learning from world-class professors in state-of-the-art laboratories is an invaluable opportunity unique to Cambridge. My individual research was focused on creating non-toxic antimicrobial coatings. Working with direct support from my supervisor helped me develop necessary technical and soft skills for careers within and beyond academia. Both the individual and team research projects, in addition to the taught modules, focused on solving current issues within the biotechnology sector. I appreciated the flexibility to tailor the taught modules to our own individual passions and pursuits with topics ranging from business to biomimetics. 

Having a close-knit cohort not only gives you insight to different Colleges around Cambridge, but also into different countries and cultures around the world. The town of Cambridge is big enough where there is always something to do, but small enough where it felt like home shortly after arriving. I am confident the professional and personal relationships formed with members of my cohort, supervisors, and students in and out of the department will last well beyond our time in Cambridge. Following graduation, I will begin my training to serve as a U.S. Navy Pilot.

Dillon Chew ( Singapore, Class of 2019-2020)

I came into the MPhil in Biotechnology programme with a background in Chemical Engineering and the Life Sciences. During my undergraduate time, I had several opportunities to work on design and research projects focusing on the sustainable bioproduction of chemicals and biofuels, which greatly sparked my interest in the application of biology to develop technologies that would improve our everyday lives. 

Coming across the MPhil in Biotechnology at Cambridge, I was drawn to the interdisciplinary nature, half-taught half-research curriculum, and close connections that the progarmme has with the biotechnology industry. In addition, it was very hard to reject the opportunity to live the Cambridge experience.

The interdisciplinary and application-focused nature was what made the program challenging and rewarding. For instance, both the Healthcare Biotechnology and Bionanotechnology courses challenged us to develop diagnostic solutions for the pandemic. One of the most enjoyable experiences I had in the porgarmme was my individual research project under Professor Alison Smith from the Department of Plant Sciences, which really complimented my previous experiences. The project not only allowed me to further hone my wet lab skills, but also challenged me to venture into the world of bioinformatics which greatly expanded my technical skill set. In addition, the research group was also very accommodating, and I really appreciated the support and all the intellectual discussions we had.

Outside of class, I also had valuable experiences working with other undergraduate and postgraduate students in the area of biotechnology. Getting involved with the Cambridge Consulting Network, I worked with biotech startups to understand their needs and directly propose solutions for them. In addition, joining the Medical iTeams allowed me gain hands-on experience as I developed commercialisation approaches for an innovative medical invention.  

Currently, I am working as an associate scientist at Procter and Gamble where I integrate microbiology, molecular biology and bioinformatics to drive innovation in the hygiene space. Some interesting projects include developing rapid/real-time hygiene diagnostic technologies, upgrading the microbial efficacy of hygiene products, and studying the microbiomes around us through metagenomics sequencing. 

I strongly believe that my time at Cambridge has greatly exposed me to the rapidly growing field of biotechnology and prepared me well for a career in this field, and I look forward to seeing where my journey in biotechnology takes me.

Maxime Crabé ( France, Class of 2018-2019)

I decided to apply for the MPhil in Biotechnology because of its broad range of electives, close connections with the industry, and to live the Cambridge experience!

The course made me discover how broad the field of biotechnology actually is, and how diverse your career possibilities are. Working in an academic lab or becoming an entrepreneur are two very different career plans that appeal to me, and this MPhil gave me an exposure to both of them.

The most enjoyable part of the MPhil was my individual research project. I was fully integrated within my team, the Bionano Engineering Group of Dr Ljiljana Fruk, and received all the support I needed to carry out my own research project.

Throughout the course I had the opportunity to meet a lot of enthusiastic and passionate researchers working in different academic or industrial labs. I might come back to Cambridge to work with some of them in the years to come!

I am now working as a strategy consultant for the biotech/pharmaceutical industry and thus advising executives on high-level decisions covering a broad range of issues. For instance, projects I have been working on include the development of a 5-year business plan for a company developing software-assisted genetic diagnoses for precision medicine, the optimisation of a big pharma's R&D productivity, and the preparation of the commercial launch of a new cancer treatment. With its balance between scientific and business-oriented electives, the MPhil in Biotechnology definitely equipped me with all of the necessary knowledge I need in my daily practice!

Wilson Wang ( US, Class of 2018-2019)

After specialising in chemistry during my last year at Williams College in the USA, I knew I wanted to see more of how science moves from theory to application. A rigorous education in the science and business of biotechnology in the innovation hub of Silicon Fen was the perfect way for me to do this.

The MPhil in Biotechnology added a new layer to what I plan to do in the future. Although I aspired to pursue medicine in an MD degree in the USA, I wanted to add an extra layer of biotechnology onto my responsibilities as a physician. I see biotechnology as a way to help future patients.

Since leaving Cambridge, I have matriculated at the Washington University School of Medicine in St. Louis as a Distinguished Student Scholar. I have recently completed my first year of medical school (virtually as per Covid) and am preparing to enter the hospitals soon to apply my knowledge practically in clinical rotations. The pandemic has only re-emphasized the importance of scientific research and its translation and application to society, and so I continue to explore new ways of adding that extra layer of biotechnology and entrepreneurship as I train as an aspiring physician.

A basis for further study or a move into industry

Some of the hottest careers in science are linked to the rapid advances in the biotech sector. The MPhil in Biotechnology will equip you with the right set of skills to pursue a career in the pharmaceutical, healthcare, agritech, or bioenergy industries, or in other sectors where bioprocesses are important.

It may also be a stepping stone to PhD level studies. With us, you will acquire core and advanced knowledge in biotechnology, explore current trends and look at the latest technologies in relevant areas, gain a wide range of practical and transferable skills, and develop business awareness.

Tailored to your personal career goals

The programme’s structure and content are flexible so that you can tailor your studies to your interests and career goals by selecting your specialised modules and the area and department within the University in which you would like to carry out your research project.

As a student at the University of Cambridge you will have access to our exceptional Careers Service . This service provides general career planning advice, organises recruitment events that attract major global companies and high-profile employers, and offers one-to-one sessions with its careers advisers. The programme's faculty and industry champions are also available to provide career advice in their area of specialisation.

Cambridge: a rapidly growing biotech hub

Our MPhil in Biotechnology incorporates the cutting-edge research being developed at the University of Cambridge, it has been designed in consultation with employers to take into consideration the workforce needs and skills gaps in the field, and it is continuously updated with the input from our industry champions.

The University of Cambridge is well known by the talent pool it generates, and its graduates are amongst the world’s most sought-after by employers.

As a natural result of its academic strength, the University of Cambridge has an enviable track record of spin-outs in biotech-related areas. Learn more about the University’s efforts to aid the transfer of knowledge through commercialisation from Cambridge Enterprise .

Throughout the programme your will have plenty of opportunities to interact with classmates and other colleagues, alumni, a diversity of world-class academics and our industry champions and visitors. University-wide events (e.g. extra-curricular entrepreneurship activities) and the fact that Cambridge is home to one of the most important biotech clusters in Europe will also create great networking opportunities.

Entry requirements

Candidate profile.

The programme is designed primarily for those who intend to develop interdisciplinary skills and apply their backgrounds in engineering, physics, chemistry, maths or computer sciences in the biotech sector. A degree in these areas is normally expected, but strong candidates with other backgrounds will also be considered.

Entry to the MPhil in Biotechnology is very competitive, with the programme attracting applications from top quality students from across the world. We aim to admit highly motivated, perseverant, hard-working students, who are critical thinkers and enthusiastic about integrating scattered data and knowledge from different fields. We expect applicants to be able to demonstrate to the selection panel a high level of commitment, irrespective of formal academic qualifications.

We are committed to offering a diverse and inclusive environment, and welcome applications from under-represented groups, fully aligning with the University’s policies on equality and diversity. All applications are evaluated on the basis of academic merit.

Expected academic standard

Applicants should have achieved a UK first class or high upper second class honours degree or equivalent. If your degree is not from the UK, please consult the International section of the Postgraduate Admissions Prospectus to find the equivalent standard in your country.

Competence in English

Candidates who are not native English speakers must demonstrate that they can read, write and speak English to the standard required to fully participate in the programme. Information on the language test scores required for the MPhil in Biotechnology can be found in the International section of the Postgraduate Admissions Prospectus. Specifically, the requirements for IELTS and TOEFL are:

IELTS (Academic): minimum overall score of 7.0, with a minimum of 7.0 in the listening, writing and speaking elements, and a minimum of 6.5 in the reading element.

TOEFL (Internet Score): minimum overall score of 100, with no less than 25 in each element.

How to apply

Admissions for entry in October 2024 are open from 4 September 2023 until 25 June 2024, but we encourage candidates to apply as soon as conveniently possible. Please note that other specific funding deadlines may be in place.

Further detailed information can be found in the University’s Postgraduate Studies Prospectus . For enquiries about admissions or if you would like to get additional information about the programme before applying, please contact us .

Application process

Applications are handled centrally by the Postgraduate Admissions Office, which provides full information on the application process, including deadlines, admission criteria, colleges and funding, as well as on the post-application stage.

Upon application, you will be required to provide your transcripts, evidence of competence in English , your CV/resume, and details of two academic referees who will be contacted by the University to supply references . You will also need to provide a statement of interest (1500 characters) and explain your reasons for applying for the MPhil in Biotechnology (1500 characters). Note that additional elements may be required to apply for specific funding schemes (please refer to the Postgraduate Studies Prospectus ).

After submitting an application, shortlisted candidates will be interviewed (normally by video call) before the Department formally recommends an offer of admission.

Completed applications are considered in sequence by the Department, the Degree Committee and the Postgraduate Admissions Office, and the duration of the process within each of these varies . Most of the applications are considered by the Department within 8 weeks of all required elements (including the academic references) being submitted. Many applicants receive a decision much earlier than this.

Early application is strongly recommended as we operate a continuous admission process, meaning that places on the programme are allocated on an ongoing basis throughout the year.

Finances and funding

Students enrolled in the programme must have funds available to pay fees and maintenance costs (please refer to the  Finance section  of the Postgraduate Studies Prospectus).

There is currently no specific funding being advertised for the MPhil in Biotechnology. Applicants may be eligible to apply for the general funding opportunities from across the collegiate University (please see the  Funding section  of the Postgraduate Studies Prospectus). The  Postgraduate Funding Search tool  will help you finding out which type of funding you might be eligible for, and how and when to apply.

Please note that the application deadline for some funding schemes may be much earlier than that advertised for the programme admissions in late June.

If you have any questions about the programme or studying at the University of Cambridge that are not answered in this website, the University Course Directory or the online Postgraduate Studies Prospectus , please do get in touch with us using our online form .

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Explore our undergraduate course, taught postgraduate programmes, and research opportunities.

Driven by curiosity. Driving change.

Computational and Systems Biology

77 Massachusetts Avenue Building 68-230A Cambridge MA, 02139

617-324-4144 [email protected]

Website: Computational and Systems Biology

Application Opens: October 1

Deadline: December 1 at 11:59 PM Eastern Time

Fee: $90.00

Terms of Enrollment

Fall Term (September)

Doctor of Philosophy (PhD)

Standardized Tests

Graduate Record Examination (GRE) is not required.

International English Language Testing System (IELTS)

• Minimum score required: 7
• Electronic scores send to: MIT Graduate Admissions

Test of English as a Foreign Language (TOEFL)

• Minimum score required: 100 (iBT) 600 (PBT)
• Institute code: 3514
• Department code: 99

Waivers of IELTS/TOEFL may be available.

*IELTS Indicator Test also accepted.

Areas of Research

• Behavioral Genetics and Genomics
• Bioengineering and Neuroengineering
• Quantitative Imaging
• Biological Networks and Machine Learning
• Cancer Systems Biology
• Cellular Biophysics
• Chemical Biology and Metabolomics
• Epigenomics
• Evolutionary and Computational Biology
• Microbiology and Systems Ecology
• Single Cell Manipulations and Measurement
• Molecular Biophysics and Structural Biology
• Precision Medicine and Medical Genomics
• Regulatory Genomics and Proteomics
• Stem Cell and Developmental Systems Biology
• Synthetic Biology and Biological Design

Financial Support

All CSB students are fully supported until they complete all the requirements of the PhD program. This support may come from sources such as a NIH T32 Training Grant; federally-sponsored fellowships from the NSF, DOD, DOD NDSEG, and DOE CSGF; and fellowships and awards from international organizations. Please see the CSB website for more information.

Application Requirements

• Online application
• Statement of objectives
• Three letters of recommendation
• Transcripts
• English proficiency exam scores

Special Instructions

Applicants are not required to complete the Subjects Taken page. All other sections are required. We generally do not review CVs, as information can be included in your online application.

This site uses cookies to give you the best possible experience. By browsing our website, you agree to our use of cookies.

If you require further information, please visit the Privacy Policy page.

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Cambridge centre for data-driven discovery, undergraduate .

C2D3 Computational Biology members have helped set up, run and teach relevant undergraduate courses including Molecular Bioengineering I (Engineering 3G1) and the Part III in Systems Biology. Molecular Bioengineering II (Engineering 4G8) will run for the first time in Lent 2024. They have also co-organised the Cambridge team for the International Genetically Engineered Machines (iGEM) competition from 2005-2012 and 2014, winning many prizes including the Grand Prize in 2009. 

MPhil degree in Computational Biology

The MPhil in Computational Biology is an 11-month course aimed at introducing students to quantitative aspects of biological and medical sciences, including bioinformatics. It is intended for mathematicians, computer scientists and others with similar backgrounds wishing to learn about the subject in preparation for a PhD course or a career in industry. It is also suitable for students with a first degree in biosciences as long as they have strong quantitative skills (which should be documented in their application). 

Wellcome Trust PhD Programme in Mathematical Genomics and Medicine (MGM) 

This programme is no longer recruiting.  

Enquiries:  [email protected]  

Programme Director: Professor Richard Durbin (Genetics; Wellcome Sanger Institute)

Deputy Directors: 

• Dr Hilary Martin (Wellcome Sanger Institute)
• Prof. Gos Micklem  (C2D3 Computational Biology; DAMTP; Genetics)
• Prof. Marc Tischkowitz  (Medical Genetics)
• Dr Chris Wallace (Medicine; MRC Biostatistics Unit)

Modern genomics promises not only to help uncover the molecular basis of disease, but also to have a major impact on health care through translation of advances in techniques, computation and knowledge into clinical trials and clinical practice. Quantitative analysis is at the heart of this goal, and there is a pressing requirement for researchers with thorough mathematical and statistical expertise, in addition to training in medical genetics and informatics. 

This PhD programme has been established as a collaboration between the University and the Wellcome Trust Sanger Institute. The programme will provide the opportunity to work at the interface between the mathematical and computational sciences, and genome-scale and translational medical research. We expect that successful applicants will have strong mathematical, statistical and computational skills, and may include exceptional biologists. They will develop quantitative techniques and theoretical approaches and apply them to practical problems in both translational and basic biomedical research. The programme follows a "1 + 3" model, comprising a tailored first year of taught modules and research rotations, followed by a three-year research project. All students will have two supervisors, one from a mathematics, engineering or other quantitative science background, and the second from a genetics or genomics/biomedical background. 

Successful applicants will have the opportunity to undertake research that draws on the unique strengths of the Cambridge region: the successful synergies of NHS and University in translational medical research; genetics, computational and genomics research at the University and the Wellcome Trust Sanger Institute; and the University’s outstanding research and training base in the mathematical sciences. 

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

• Supports and connects the growing data science and AI research community 
• Builds research capacity in data science and AI to tackle complex issues 
• Drives new research challenges through collaborative research projects 
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• Identifies and provides training courses for students, academics, industry and the third sector 
• Serves as a gateway for external organisations 

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Center for Computational Biology

Computational Biology PhD

The main objective of the Computational Biology PhD is to train the next generation of scientists who are both passionate about exploring the interface of computation and biology, and committed to functioning at a high level in both computational and biological fields.

The program emphasizes multidisciplinary competency, interdisciplinary collaboration, and transdisciplinary research, and offers an integrated and customizable curriculum that consists of two semesters of didactic course work tailored to each student’s background and interests, research rotations with faculty mentors spanning computational biology’s core disciplines, and dissertation research jointly supervised by computational and biological faculty mentors.

The Computational Biology Graduate Group facilitates student immersion into UC Berkeley’s vibrant computational biology research community. Currently, the Group includes over 46 faculty from across 14 departments of the College of Letters and Science, the College of Engineering, the College of Natural Resources, and the School of Public Health. Many of these faculty are available as potential dissertation research advisors for Computational Biology PhD students, with more available for participation on doctoral committees.

The First Year

The time to degree (normative time) of the Computational Biology PhD is five years. The first year of the program emphasizes gaining competency in computational biology, the biological sciences, and the computational sciences (broadly construed). Since student backgrounds will vary widely, each student will work with faculty and student advisory committees to develop a program of study tailored to their background and interests. Specifically, all first-year students must:

• Perform three rotations with Core faculty (one rotation with a non-Core faculty is acceptable with advance approval)
• Complete course work requirements (see below)
• Complete a course in the Responsible Conduct of Research
• Attend the computational biology seminar series
• Complete experimental training (see below)

Laboratory Rotations

Entering students are required to complete three laboratory rotations during their first year in the program to seek out a Dissertation Advisor under whose supervision dissertation research will be conducted. Students should rotate with at least one computational Core faculty member and one experimental Core faculty member. Click here to view rotation policy. 

Course Work & Additional Requirements

Students must complete the following coursework in the first three (up to four) semesters. Courses must be taken for a grade and a grade of B or higher is required for a course to count towards degree progress:

• Fall and Spring semester of CMPBIO 293, Doctoral Seminar in Computational Biology
• A Responsible Conduct of Research course, most likely through the Department of Molecular and Cell Biology.
• STAT 201A & STAT 201B : Intro to Probability and Statistics at an Advanced Level. Note: Students who are offered admission and are not prepared to complete STAT 201A and 201B will be required to complete STAT 134 or PH 142 first.
• CS61A : The Structure and Interpretation of Computer Programs. Note: students with the equivalent background can replace this requirement with a more advanced CS course of their choosing.
• 3 elective courses relevant to the field of Computational Biology , one of which must be at the graduate level (see below for details).
• Attend the computational biology invited speaker seminar series. A schedule is circulated to all students by email and is available on the Center website. Starting with the 2023 entering class, CCB PhD students must enroll in CMPBIO 275: Computational Biology Seminar , which provides credit for this seminar series.
• 1) completion of a laboratory course at Berkeley with a minimum grade of B,
• 2) completion of a rotation in an experimental lab (w/ an experimental project), with a positive evaluation from the PI,
• a biological sciences undergraduate major with at least two upper division laboratory-based courses,
• a semester or equivalent of supervised undergraduate experimental laboratory-based research at a university,
• or previous paid or volunteer/internship work in an industry-based experimental laboratory.

Students are expected to develop a course plan for their program requirements and to consult with the Head Graduate Advisor before the Spring semester of their first year for formal approval (signature required). The course plan will take into account the student’s undergraduate training areas and goals for PhD research areas.

Satisfactory completion of first year requirements will be evaluated at the end of the spring semester of the first year. If requirements are satisfied, students will formally choose a Dissertation advisor from among the core faculty with whom they rotated and begin dissertation research.

Waivers: Students may request waivers for the specific courses STAT 201A, STAT 201B, and CS61A. In all cases of waivers, the student must take alternative courses in related areas so as to have six additional courses, as described above. For waiving out of STAT 201A/B, students can demonstrate they have completed the equivalent by passing a proctored assessment exam on Campus. For waiving out CS61A, the Head Graduate Advisor will evaluate student’s previous coursework based on the previous course’s syllabus and other course materials to determine equivalency.

Electives: Of the three electives, students are required to choose one course in each of the two following cluster areas:

• Cluster A (Biological Science) : These courses are defined as those for which the learning goals are primarily related to biology. This includes courses covering topics in molecular biology, genetics, evolution, environmental science, experimental methods, and human health. This category may also cover courses whose focus is on learning how to use bioinformatic tools to understand experimental data.
• Cluster B (Computational Sciences): These courses are defined as those for which the learning goals involve computing, inference, or mathematical modeling, broadly defined. This includes courses on algorithms, computing languages or structures, mathematical or probabilistic concepts, and statistics. This category would include courses whose focus is on biological applications of such topics.

In the below link we give some relevant such courses, but students can take courses beyond this list; for courses not on this list, the Head Graduate Advisor will determine to which cluster a course can be credited. For classes that have significant overlap between these two clusters, the department which offers the course may influence the decision of the HGA as to whether the course should be assigned to cluster A or B.

See below for some suggested courses in these categories:

Suggested Coursework Options

Second Year & Beyond

At the beginning of the fall of the second year, students begin full-time dissertation research in earnest under the supervision of their Dissertation advisor. It is anticipated that it will take students three (up to four) semesters to complete the 6 course requirement. Students are required to continue to participate annually in the computational biology seminar series.

Qualifying Examination

Students are expected to take and pass an oral Qualifying Examination (QE) by the end of the spring semester (June 15th) of their second year of graduate study. Students must present a written dissertation proposal to the QE committee no fewer than four weeks prior to the oral QE. The write-up should follow the format of an NIH-style grant proposal (i.e., it should include an abstract, background and significance, specific aims to be addressed (~3), and a research plan for addressing the aims) and must thoroughly discuss plans for research to be conducted in the dissertation lab. Click here for more details on the guidelines and format for the QE. Click here to view the rules for the composition of the committee and the form for declaring your committee.

Advancement to Candidacy

After successfully completing the QE, students will Advance to Candidacy. At this time, students select the members of their dissertation committee and submit this committee for approval to the Graduate Division. Students should endeavor to include a member whose research represents a complementary yet distinct area from that of the dissertation advisor (ie, biological vs computational, experimental vs theoretical) and that will be integrated in the student’s dissertation research. Click here to view the rules for the composition of the committee and the form for declaring your committee.

Meetings with the Dissertation Committee

After Advancing to Candidacy, students are expected to meet with their Dissertation Committee at least once each year.

Teaching Requirements

Computational Biology PhD students are required to teach at least two semesters (starting with Fall 2019 class), but may teach more. The requirement can be modified if the student has funding that does not allow teaching. Starting with the Fall 2019 class: At least one of those courses should require that you teach a section. Berkeley Connect or CMPBIO 293 can count towards one of the required semesters.

The Dissertation

Dissertation projects will represent scholarly, independent and novel research that contributes new knowledge to Computational Biology by integrating knowledge and methodologies from both the biological and computational sciences. Students must submit their dissertation by the May Graduate Division filing deadline (see Graduate Division for date) of their fifth–and final–year.

Special Requirements

Students will be required to present their research either orally or via a poster at the annual retreat beginning in their second year.

• Financial Support

The Computational Biology Graduate Group provides a competitive stipend as well as full payment of fees and non-resident tuition (which includes health care). Students maintaining satisfactory academic progress are provided full funding for five to five and a half years. The program supports students in the first year, while the PI/mentor provides support from the second year on. A portion of this support is in the form of salary from teaching assistance as a Graduate Student Instructor (GSI) in allied departments, such as Molecular and Cell Biology, Integrative Biology, Plant and Microbial Biology, Mathematics, Statistics or Computer Science. Teaching is part of the training of the program and most students will not teach more than two semesters, unless by choice.

Due to cost constraints, the program admits few international students; the average is two per year. Those admitted are also given full financial support (as noted above): stipend, fees and tuition.

Students are also strongly encouraged to apply for extramural fellowships for the proposal writing experience. There are a number of extramural fellowships that Berkeley students apply for that current applicants may find appealing. Please note that the NSF now only allows two submissions – once as an undergrad and once in grad school. The NSF funds students with potential, as opposed to specific research projects, so do not be concerned that you don’t know your grad school plans yet – just put together a good proposal! Although we make admissions offers before the fellowships results are released, all eligible students should take advantage of both opportunities to apply, as it’s a great opportunity and a great addition to a CV.

• National Science Foundation Graduate Research Fellowship (app deadlines in Oct)
• Hertz Foundation Fellowship (app deadline Oct)
• National Defense Science and Engineering Graduate Fellowship (app deadline in mid-Fall)
• DOE Computational Science Graduate Fellowship (Krell Institute) (app deadline in Jan)

CCB no longer requires the GRE for admission (neither general, nor subject). The GRE will not be seen by the review committee, even if sent to Berkeley.

PLEASE NOTE: The application deadline is Monday, December 2 , 2024, 8:59 PST/11:59 EST

We invite applications from students with distinguished academic records, strong foundations in the basic biological, physical and computational sciences, as well as significant computer programming and research experience. Admission for the Computational Biology PhD is for the fall semester only, and Computational Biology does not offer a Master’s degree.

We are happy to answer any questions you may have, but please be sure to read this entire page first, as many of your questions will be answered below or on the Tips tab.

IMPORTANT : Please note that it is not possible to select a specific PhD advisor until the end of the first year in the program, so contacting individual faculty about openings in their laboratories will not increase your chances of being accepted into the program. You will have an opportunity to discuss your interests with relevant faculty if you are invited to interview in February.

Undergraduate Preparation

Minimum requirements for admission to graduate study:

• A bachelor’s degree or recognized equivalent from an accredited institution.
• Minimum GPA of 3.0.
• Undergraduate preparation reflecting a balance of training in computational biology’s core disciplines (biology, computer science, statistics/mathematics), for example, a single interdisciplinary major, such as computational biology or bioinformatics; a major in a core discipline and a combination of interdisciplinary course work and research experiences; or a double major in core disciplines.
• Basic research experience and aptitude are key considerations for admission, so evidence of research experience and letters of recommendation from faculty mentors attesting to the applicant’s research experience are of particular interest.
• GRE – NOT required or used for review .
• TOEFL scores for international students (see below for details).

Application Requirements

ALL materials, including letters, are due December 2, 2024 (8:59 PST). More information is provided and required as part of the online application, so please create an account and review the application before emailing with questions (and please set up an account well before the deadline):

• A completed graduate application: The online application opens in early or mid-September and is located on the Graduate Division website . Paper applications are not accepted. Please create your account and review the application well ahead of the submit date , as it will take time to complete and requests information not listed here.
• A nonrefundable application fee: The fee must be paid using a major credit card and is not refundable. For US citizens and permanent residents, the fee is $135; US citizens and permanent residents may request a fee waiver as part of the online application. For all other students (international) the fee is $155 (no waivers, no exceptions). Graduate Admissions manages the fee, not the program, so please contact them with questions.
• Three letters of recommendation, minimum (up to five are accepted): Letters of recommendation must be submitted online as part of the Graduate Division’s application process. Letters are also due Dec. 2, so please inform your recommenders of this deadline and give them sufficient advance notice. It is your responsibility to monitor the status of your letters of recommendation (sending prompts, as necessary) in the online system.
• Transcripts: Unofficial copies of all relevant transcripts, uploaded as part of the online application (see application for details). Scanned copies of official transcripts are strongly preferred, as transcripts must include applicant and institution name and degree goal and should be easy for the reviewers to read (print-outs from online personal schedules can be hard to read and transcripts without your name and the institution name cannot be used for review). Do not send via mail official transcripts to Grad Division or Computational Biology, they will be discarded.
• Essays: Follow links to view descriptions of what these essays should include ( Statement of Purpose [2-3 pages], Personal Statement [1-2 pages]). Also review Tips tab for formatting advice.
• (Highly recommended) Applicants should consider applying for extramural funding, such as NSF Fellowships. These are amazing opportunities and the application processes are great preparation for graduate studies. Please see Financial Support tab.
• Read and follow all of the “Application Tips” listed on the last tab. This ensures that everything goes smoothly and you make a good impression on the faculty reviewing your file.

The GRE general test is not required. GRE subject tests are not required. GRE scores will not be a determining factor for application review and admission, and will NOT be seen by the CCB admissions committee. While we do not encourage anyone to take the exam, in case you decide to apply to a different program at Berkeley that does require them: the UC Berkeley school code is 4833; department codes are unnecessary. As long as the scores are sent to UC Berkeley, they will be received by any program you apply to on campus.

TOEFL/IELTS

Adequate proficiency in English must be demonstrated by those applicants applying from countries where English is not the official language. There are two standardized tests you may take: the Test of English as a Foreign Language (TOEFL), and the International English Language Testing System (IELTS). TOEFL minimum passing scores are 90 for the  Internet-based test (IBT) , and 570 for the paper-based format (PBT) . The TOEFL may be waived if an international student has completed at least one year of full-time academic course work with grades of B or better while in residence at a U.S. university (transcript will be required). Please click here for more information .

Application Deadlines

The Application Deadline is 8:59 pm Pacific Standard Time, December 2, 2024 . The application will lock at 9pm PST, precisely. All materials must be received by the deadline. While rec letters can continue to be submitted and received after the deadline, the committee meets in early December and will review incomplete applications. TOEFL tests should be taken by or before the deadline, but self-reported scores are acceptable for review while the official scores are being processed. All submitted applications will be reviewed, even if materials are missing, but it may impact the evaluation of the application.

It is your responsibility to ensure and verify that your application materials are submitted in a timely manner. Please be sure to hit the submit button when you have completed the application and to monitor the status of your letters of recommendation (sending prompts, as necessary). Please include the statement of purpose and personal statement in the online application. While you can upload a CV, please DO NOT upload entire publications or papers. Please DO NOT send paper résumés, separate folders of information, or articles via mail. They will be discarded unread.

The Computational Biology Interview Visit dates are yet to be determined, but will be posted here once they are.

Top applicants who are being considered for admission will be invited to visit campus for interviews with faculty. Invitations will be made by early January. Students are expected to stay for the entire event, arriving in Berkeley by 5:30pm on the first day and leaving the evening of the final day. In the application, you must provide the names of between 7-10 faculty from the Computational Biology website with whom you are interested in conducting research or performing rotations. This helps route your application to our reviewers and facilitates the interview scheduling process. An invitation is not a guarantee of admission.

International students may be interviewed virtually, as flights are often prohibitively expensive.

Tips for the Application Process

Uploaded Documents: Be sure to put your name and type of essay on your essays ( Statement of Purpose [2-3 pages], Personal Statement [1-2 pages]) as a header or before the text, whether you use the text box or upload a PDF or Word doc. There is no minimum length on either essay, but 3 pages maximum is suggested. The Statement of Purpose should describe your research and educational background and aspirations. The Personal Statement can include personal achievements not necessarily related to research, barriers you’ve had to overcome, mentoring and volunteering activities, things that make you unique and demonstrate the qualities you will bring to the program.

Letters of Recommendation: should be from persons who have supervised your research or academic work and who can evaluate your intellectual ability, creativity, leadership potential and promise for productive scholarship. If lab supervision was provided by a postdoc or graduate student, the letter should carry the signature or support of the faculty member in charge of the research project. Note: the application can be submitted before all of the recommenders have completed their letters. It is your responsibility to keep track of your recommender’s progress through the online system. Be sure to send reminders if your recommenders do not submit their letters.

Extramural fellowships: it is to your benefit to apply for fellowships as they may facilitate entry into the lab of your choice, are a great addition to your CV and often provide higher stipends. Do not allow concerns about coming up with a research proposal before joining a lab prevent you from applying. The fellowships are looking for research potential and proposal writing skills and will not hold you to specific research projects once you have started graduate school.

Calculating GPA: Schools can differ in how they assign grades and calculate grade point averages, so it may be difficult for this office to offer advice. The best resource for calculating the GPA for your school is to check the back of the official transcripts where a guide is often provided or use an online tool. There are free online GPA conversion tools that can be found via an internet search.

Faculty Contact/Interests: Please be sure to list faculty that interest you as part of the online application. You are not required to contact any faculty in advance, nor will it assist with admission, but are welcome to if you wish to learn more about their research.

Submitting the application: To avoid the possibility of computer problems on either side, it is NOT advisable to wait until the last day to start and/or submit your application. It is not unusual for the application system to have difficulties during times of heavy traffic. However, there is no need to submit the application too early. No application will be reviewed before the deadline.

Visits: We only arrange one campus visit for recruitment purposes. If you are interested in visiting the campus and meeting with faculty before the application deadline, you are welcome to do so on your own time (we will be unable to assist).

Name: Please double check that you have entered your first and last names in the correct fields. This is our first impression of you as a candidate, so you do want to get your name correct! Be sure to put your name on any documents that you upload (Statement of Purpose, Personal Statement).

California Residency: You are not considered a resident if you hope to enter our program in the Fall, but have never lived in California before or are here on a visa. So, please do not mark “resident” on the application in anticipation of admission. You must have lived in California previously, and be a US citizen or Permanent Resident, to be a resident.

Faculty Leadership Head Graduate Advisor and Chair for the PhD & DE John Huelsenbeck ( [email protected] )

Associate Head Graduate Advisor for PhD & DE Liana Lareau ( [email protected] )

Equity Advisor Rasmus Nielsen ( [email protected] )

Director of CCB Elizabeth Purdom ( [email protected] )

Core PhD & DE Faculty ( link )

Staff support Student Services Advisor (GSAO): Kate Chase ( [email protected] )

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MPhil in Biotechnology

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Course closed:

Biotechnology is no longer accepting new applications.

The MPhil in Biotechnology is a unique programme that draws on world-leading academics and industry champions to deliver a multidisciplinary curriculum at the interface of biology with the physical sciences and technology. Providing state-of-the-art education and research training in cutting-edge areas, the programme was designed to respond to major talent needs and skills gaps in the biotech sector.

In the programme, students acquire foundational and advanced knowledge in biotechnology, and gain practical and research skills for wet-lab and computer-based work. The programme also promotes the development of transferable skills and business competences that are relevant to biotechnology research and industry practice.

Overall, the programme aims to produce graduates who have the fundamental understanding of biotechnology and skills all the way from the lab bench to the market place, who will go on to become leaders in the fast-growing biotech sector and its satellite fields.

The programme offers students the possibility of tailoring their studies to their interests, educational needs and career goals.

Learning Outcomes

The MPhil in Biotechnology equips students with the knowledge and the skills that are necessary to pursue a career in the pharmaceutical, healthcare, agritech, or bioenergy sectors, or in other areas where bioprocesses are important, either in academic or industry settings. 

At the end of the programme, students will demonstrate foundational and advanced knowledge of biotechnology . They will have received a technical grounding in core topics, explored current trends and looked at the latest technologies in biotechnology . Upon conclusion of the programme, students will also show proficiency at practical work in biotechnology , and be aware of modern bioanalytical techniques and their limitations .

With a strong research component, the programme will prepare students to undertake a research project that requires understanding of a wide range of techniques and published literature, originality in the application of knowledge, and self-direction .

The programme promotes the development of diverse transferable skills. In particular, graduating students will be able to communicate by formal reports and oral presentations at a high standard, effectively manage tasks and work to deadlines , and collaborate as part of a team . Additionally, they will be aware of the best practices in research data management  and understand the scientific publishing process as well as the need to be able to communicate science in outreach contexts . The successful students will also demonstrate a degree of business awareness that is important for roles in the biotechnology sector , allowing them to effectively communicate and interact with a range of stakeholders. In particular, they will understand the process of transforming new technologies and ideas into marketable products, have an idea of the main issues in translational research, and be acquainted with intellectual property and bioethics key concepts.

This is a stand-alone MPhil programme, which cannot be counted as the first year of a PhD degree. Strong students on the programme can apply for a PhD place at the Department of Chemical Engineering and Biotechnology or at other departments in the University.

The Postgraduate Virtual Open Day usually takes place at the end of October. It is a great opportunity to ask questions to admissions staff and academics, to explore the Colleges, and to find out more about courses, the application process and funding opportunities. Visit the  Postgraduate Open Day  page for more details.

Beyond the Open Day, prospective students are welcome to get in touch by email at any time of the year if they wish to request further information about the programme.

Key Information

11 months full-time, study mode : taught, master of philosophy, department of chemical engineering and biotechnology, course - related enquiries, application - related enquiries, course on department website, dates and deadlines:, michaelmas 2024 (closed).

Some courses can close early. See the Deadlines page for guidance on when to apply.

Funding Deadlines

These deadlines apply to applications for courses starting in Michaelmas 2024, Lent 2025 and Easter 2025.

Similar Courses

• Chemical Engineering PhD
• Chemical Engineering and Biotechnology MPhil
• Medical Science (CRUK CI) PhD
• Cancer Biology (part-time) PhD
• Medical Science (CRUK CI) MPhil

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Computational systems biology uses computational and mathematical modeling to study complex biological systems at the molecular, cellular, and tissue levels. It combines techniques from biology, computer science, mathematics, and physics to develop models of biological processes and systems, with the goal of understanding how biological systems function and how they are perturbed in disease. Computational systems biology employs a range of tools, including mathematical modeling, simulation, data analysis, and machine learning, to integrate experimental data from a variety of sources, including genomics, proteomics, and metabolomics, into comprehensive models of biological processes. These models can then be used to make predictions about the behavior of biological systems under different conditions, and to identify potential targets for drug development and disease intervention.

Focus Areas

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